Overview

Dataset statistics

Number of variables6
Number of observations13730000
Missing cells21710000
Missing cells (%)26.4%
Duplicate rows24
Duplicate rows (%)< 0.1%
Total size in memory628.5 MiB
Average record size in memory48.0 B

Variable types

Categorical6

Alerts

Dataset has 24 (< 0.1%) duplicate rowsDuplicates
uuid has a high cardinality: 1373 distinct values High cardinality
price_string has a high cardinality: 248 distinct values High cardinality
product_type has a high cardinality: 321 distinct values High cardinality
level_1 has a high cardinality: 595 distinct values High cardinality
price_string_unf is highly correlated with categoryHigh correlation
category is highly correlated with price_string_unfHigh correlation
price_string_unf is highly correlated with categoryHigh correlation
category is highly correlated with price_string_unfHigh correlation
price_string has 8220000 (59.9%) missing values Missing
price_string_unf has 13420000 (97.7%) missing values Missing
uuid is uniformly distributed Uniform

Reproduction

Analysis started2022-04-28 17:51:25.912503
Analysis finished2022-04-28 17:55:59.643763
Duration4 minutes and 33.73 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

uuid
Categorical

HIGH CARDINALITY
UNIFORM

Distinct1373
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size104.8 MiB
638744a4-b0ae-4166-8cb6-5c063c862036
 
10000
32a6ce63-6ecd-46c5-84d9-4487bb13dd8b
 
10000
b524d72b-11a5-417b-be83-b33a83c81f4e
 
10000
2c7e75c2-c239-4461-a231-810c1dbcb51e
 
10000
08b5646e-16dd-4a6e-b0d8-0394a0f10d82
 
10000
Other values (1368)
13680000 

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row638744a4-b0ae-4166-8cb6-5c063c862036
2nd rowab313969-02cc-48b2-9daf-0054efb70b92
3rd rowacbd66ff-79f8-467a-91f9-108a45af5626
4th row963915d6-b2e3-4098-b242-9410593cf205
5th rowb5b68f3c-b1e0-40e5-8ee5-e2f7236c1daf

Common Values

ValueCountFrequency (%)
638744a4-b0ae-4166-8cb6-5c063c86203610000
 
0.1%
32a6ce63-6ecd-46c5-84d9-4487bb13dd8b10000
 
0.1%
b524d72b-11a5-417b-be83-b33a83c81f4e10000
 
0.1%
2c7e75c2-c239-4461-a231-810c1dbcb51e10000
 
0.1%
08b5646e-16dd-4a6e-b0d8-0394a0f10d8210000
 
0.1%
591c4d63-4e24-40da-85f1-de9d5194941610000
 
0.1%
286f629f-0b65-4c5d-b449-aea15c9d4c3e10000
 
0.1%
82807627-725a-4f1e-86f6-450c8c4ed86510000
 
0.1%
2ae004be-87fc-4a35-bb6a-1e3fe158d4e710000
 
0.1%
40de0ab8-f0d9-4ec6-af5e-c8dfaa98765610000
 
0.1%
Other values (1363)13630000
99.3%

Length

2022-04-28T23:25:59.781132image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
638744a4-b0ae-4166-8cb6-5c063c86203610000
 
0.1%
30befc6f-82f0-43b0-8ec1-bc99246f8a7210000
 
0.1%
acbd66ff-79f8-467a-91f9-108a45af562610000
 
0.1%
963915d6-b2e3-4098-b242-9410593cf20510000
 
0.1%
b5b68f3c-b1e0-40e5-8ee5-e2f7236c1daf10000
 
0.1%
389d9f75-cc3f-4bd2-94f7-93e381a3bed510000
 
0.1%
9599f1a9-d406-43eb-89f5-9b1c0af1ac9a10000
 
0.1%
35799087-f6f4-4ca2-abfe-cbb5c27d2f1a10000
 
0.1%
9b3f553e-ee4c-4e1c-822e-c8c6c1b7f02a10000
 
0.1%
6871b427-3c2c-4b3d-a304-c0a9f924439d10000
 
0.1%
Other values (1363)13630000
99.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

price_string
Categorical

HIGH CARDINALITY
MISSING

Distinct248
Distinct (%)< 0.1%
Missing8220000
Missing (%)59.9%
Memory size104.8 MiB
$0.00
 
240000
$89
 
120000
$9.99
 
100000
$3.99
 
90000
$38.00
 
80000
Other values (243)
4880000 

Length

Max length7
Median length5
Mean length5.188747731
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row$19.95
2nd row$92.00
3rd row11.50
4th row$24.99
5th row$148.00

Common Values

ValueCountFrequency (%)
$0.00240000
 
1.7%
$89120000
 
0.9%
$9.99100000
 
0.7%
$3.9990000
 
0.7%
$38.0080000
 
0.6%
$80.0080000
 
0.6%
$12.9980000
 
0.6%
$16070000
 
0.5%
$9960000
 
0.4%
$7960000
 
0.4%
Other values (238)4530000
33.0%
(Missing)8220000
59.9%

Length

2022-04-28T23:26:00.001433image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.00240000
 
4.4%
89120000
 
2.2%
9.99100000
 
1.8%
3.9990000
 
1.6%
38.0080000
 
1.5%
80.0080000
 
1.5%
12.9980000
 
1.5%
16070000
 
1.3%
75.0060000
 
1.1%
6.9960000
 
1.1%
Other values (233)4530000
82.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

price_string_unf
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct26
Distinct (%)< 0.1%
Missing13420000
Missing (%)97.7%
Memory size104.8 MiB
$6.75
30000 
$49.00
 
20000
$85 USD
 
20000
$11.99
 
20000
$10.00
 
10000
Other values (21)
210000 

Length

Max length28
Median length7
Mean length9.096774194
Min length5

Characters and Unicode

Total characters180000
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCurrent price: $359.00
2nd row$6.75
3rd row$15.00
4th row$18.95
5th row$459.99

Common Values

ValueCountFrequency (%)
$6.7530000
 
0.2%
$49.0020000
 
0.1%
$85 USD20000
 
0.1%
$11.9920000
 
0.1%
$10.0010000
 
0.1%
$198.0010000
 
0.1%
$52 USD10000
 
0.1%
$80 USD10000
 
0.1%
$50 USD10000
 
0.1%
$138.00 $96.6010000
 
0.1%
Other values (16)160000
 
1.2%
(Missing)13420000
97.7%

Length

2022-04-28T23:26:00.164740image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
usd70000
 
14.6%
6.7530000
 
6.2%
248.0020000
 
4.2%
current20000
 
4.2%
49.0020000
 
4.2%
178.0020000
 
4.2%
price20000
 
4.2%
11.9920000
 
4.2%
8520000
 
4.2%
459.9910000
 
2.1%
Other values (23)230000
47.9%

Most occurring characters

ValueCountFrequency (%)
180000
100.0%

Most occurring categories

ValueCountFrequency (%)
Control180000
100.0%

Most frequent character per category

Control
ValueCountFrequency (%)
180000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common180000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
180000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII180000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180000
100.0%

product_type
Categorical

HIGH CARDINALITY

Distinct321
Distinct (%)< 0.1%
Missing10000
Missing (%)0.1%
Memory size104.8 MiB
U2NydWJzIGFuZCBjbGVhbmluZyBjbG90aHM
 
200000
V29tZW5zIHN3aW13ZWFy
 
190000
V29tZW5zIHdvcmt3ZWFyLyBvZmZpY2Ugd2Vhcg
 
170000
UGxhbnQgYmFzZWQgUHJvdGVpbiBTdXBwbGVtZW50cw
 
150000
d29tZW5zIE91dGVyd2Vhcg
 
150000
Other values (316)
12860000 

Length

Max length54
Median length18
Mean length20.18148688
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTGFwdG9wIENvdmVycy9CYWdz
2nd rowQmFraW5nIEN1cHMgYW5kIE1hdHM
3rd rowR3VtbWllcyB2aXRhbWlucyBhbmQgbWluZXJhbHMgZm9yIGtpZHM
4th rowU2VydW1z
5th rowRWF0aW5nIFV0ZW5zaWxzL0N1dGxlcnk

Common Values

ValueCountFrequency (%)
U2NydWJzIGFuZCBjbGVhbmluZyBjbG90aHM200000
 
1.5%
V29tZW5zIHN3aW13ZWFy190000
 
1.4%
V29tZW5zIHdvcmt3ZWFyLyBvZmZpY2Ugd2Vhcg170000
 
1.2%
UGxhbnQgYmFzZWQgUHJvdGVpbiBTdXBwbGVtZW50cw150000
 
1.1%
d29tZW5zIE91dGVyd2Vhcg150000
 
1.1%
UGx1cyBzaXplIHdlYXI150000
 
1.1%
R3VtbWllcyB2aXRhbWlucyBhbmQgbWluZXJhbHMgZm9yIGFkdWx0cw150000
 
1.1%
V29tZW5zIFBhbnRz150000
 
1.1%
QnJ1c2hlcw140000
 
1.0%
RmFjaWFsIENsZWFuc2Vycw140000
 
1.0%
Other values (311)12130000
88.3%

Length

2022-04-28T23:26:00.340739image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
u2nydwjzigfuzcbjbgvhbmluzybjbg90ahm200000
 
1.5%
v29tzw5zihn3aw13zwfy190000
 
1.4%
v29tzw5zihdvcmt3zwfylybvzmzpy2ugd2vhcg170000
 
1.2%
ugxhbnqgymfzzwqguhjvdgvpbibtdxbwbgvtzw50cw150000
 
1.1%
d29tzw5zie91dgvyd2vhcg150000
 
1.1%
ugx1cybzaxplihdlyxi150000
 
1.1%
r3vtbwllcyb2axrhbwlucybhbmqgbwluzxjhbhmgzm9yigfkdwx0cw150000
 
1.1%
v29tzw5zifbhbnrz150000
 
1.1%
qnj1c2hlcw140000
 
1.0%
rmfjawfsienszwfuc2vycw140000
 
1.0%
Other values (311)12130000
88.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

level_1
Categorical

HIGH CARDINALITY

Distinct595
Distinct (%)< 0.1%
Missing50000
Missing (%)0.4%
Memory size104.8 MiB
U3dlYXRzaGlydA
 
90000
U29ja3M
 
70000
Q2xlYW5pbmcgY2xvdGg
 
70000
U3Bvb24sIEtuaWZlIGFuZCBGb3Jr
 
70000
TG9uZyBzbGVldmUgdGVl
 
60000
Other values (590)
13320000 

Length

Max length64
Median length18
Mean length18.94444444
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTGFwdG9wIENhc2U
2nd rowQmFraW5nIE1hdHMgLyBCYWtpbmcgZGlzaA
3rd rowSW1tdW5pdHkgZ3VtbWllcw
4th rowRmFjZSBTZXJ1bQ
5th rowQ2hvcHN0aWNrcw

Common Values

ValueCountFrequency (%)
U3dlYXRzaGlydA90000
 
0.7%
U29ja3M70000
 
0.5%
Q2xlYW5pbmcgY2xvdGg70000
 
0.5%
U3Bvb24sIEtuaWZlIGFuZCBGb3Jr70000
 
0.5%
TG9uZyBzbGVldmUgdGVl60000
 
0.4%
Rm9ybWFsIFBhbnRz60000
 
0.4%
TWluZXJhbCBHdW1taWVz60000
 
0.4%
TXVsdGl2aXRhbWluIGd1bW1pZXM60000
 
0.4%
UHVmZmVyIEphY2tldA60000
 
0.4%
U2hvcnQgc2xlZXZlIHRlZQ60000
 
0.4%
Other values (585)13020000
94.8%

Length

2022-04-28T23:26:00.526689image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
u3dlyxrzaglyda90000
 
0.7%
q2xlyw5pbmcgy2xvdgg70000
 
0.5%
u3bvb24sietuawzligfuzcbgb3jr70000
 
0.5%
u29ja3m70000
 
0.5%
uhvmzmvyifzlc3q60000
 
0.4%
rm9ybwfsifn1axrz60000
 
0.4%
sg9vzgll60000
 
0.4%
u3dlyxrlcg60000
 
0.4%
rgvuaw0gsmfja2v0lybucnvja2vyiephy2tlda60000
 
0.4%
sw1tdw5pdhkgz3vtbwllcw60000
 
0.4%
Other values (585)13020000
95.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

category
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct13
Distinct (%)< 0.1%
Missing10000
Missing (%)0.1%
Memory size104.8 MiB
Q2xvdGhpbmcgYW5kIEFjY2Vzc29yaWVz
3910000 
Z3JvY2VyaWVz
1610000 
SG91c2Vob2xkIGFuZCBDbGVhbmluZw
1570000 
YmVhdXR5IGFuZCBwZXJzb25hbCBjYXJl
1470000 
SGVhbHRo
990000 
Other values (8)
4170000 

Length

Max length35
Median length30
Mean length23.95553936
Min length8

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRWxlY3Ryb25pY3M
2nd rowa2l0Y2hpbmcgYW5kIGRpbmluZw
3rd rowSGVhbHRo
4th rowYmVhdXR5IGFuZCBwZXJzb25hbCBjYXJl
5th rowa2l0Y2hpbmcgYW5kIGRpbmluZw

Common Values

ValueCountFrequency (%)
Q2xvdGhpbmcgYW5kIEFjY2Vzc29yaWVz3910000
28.5%
Z3JvY2VyaWVz1610000
11.7%
SG91c2Vob2xkIGFuZCBDbGVhbmluZw1570000
11.4%
YmVhdXR5IGFuZCBwZXJzb25hbCBjYXJl1470000
 
10.7%
SGVhbHRo990000
 
7.2%
VG95cyBhbmQgR2FtZXM790000
 
5.8%
cGV0IHN1cHBsaWVz740000
 
5.4%
QmFieWNhcmU660000
 
4.8%
a2l0Y2hpbmcgYW5kIGRpbmluZw590000
 
4.3%
VG9vbHMgYW5kIGhvbWUgaW1wcm92ZW1lbnQ520000
 
3.8%
Other values (3)870000
 
6.3%

Length

2022-04-28T23:26:00.685125image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
q2xvdghpbmcgyw5kiefjy2vzc29yawvz3910000
28.5%
z3jvy2vyawvz1610000
11.7%
sg91c2vob2xkigfuzcbdbgvhbmluzw1570000
11.4%
ymvhdxr5igfuzcbwzxjzb25hbcbjyxjl1470000
 
10.7%
sgvhbhro990000
 
7.2%
vg95cybhbmqgr2ftzxm790000
 
5.8%
cgv0ihn1chbsawvz740000
 
5.4%
qmfiewnhcmu660000
 
4.8%
a2l0y2hpbmcgyw5kigrpbmluzw590000
 
4.3%
vg9vbhmgyw5kighvbwugaw1wcm92zw1lbnq520000
 
3.8%
Other values (3)870000
 
6.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Correlations

2022-04-28T23:26:00.782419image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-04-28T23:26:00.920194image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-04-28T23:24:48.831080image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-04-28T23:24:58.878390image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-04-28T23:25:26.751538image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-04-28T23:25:32.581017image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

uuidprice_stringprice_string_unfproduct_typelevel_1category
0638744a4-b0ae-4166-8cb6-5c063c862036NaNNaNTGFwdG9wIENvdmVycy9CYWdzTGFwdG9wIENhc2URWxlY3Ryb25pY3M
1ab313969-02cc-48b2-9daf-0054efb70b92NaNNaNQmFraW5nIEN1cHMgYW5kIE1hdHMQmFraW5nIE1hdHMgLyBCYWtpbmcgZGlzaAa2l0Y2hpbmcgYW5kIGRpbmluZw
2acbd66ff-79f8-467a-91f9-108a45af5626$19.95NaNR3VtbWllcyB2aXRhbWlucyBhbmQgbWluZXJhbHMgZm9yIGtpZHMSW1tdW5pdHkgZ3VtbWllcwSGVhbHRo
3963915d6-b2e3-4098-b242-9410593cf205$92.00NaNU2VydW1zRmFjZSBTZXJ1bQYmVhdXR5IGFuZCBwZXJzb25hbCBjYXJl
4b5b68f3c-b1e0-40e5-8ee5-e2f7236c1daf11.50NaNRWF0aW5nIFV0ZW5zaWxzL0N1dGxlcnkQ2hvcHN0aWNrcwa2l0Y2hpbmcgYW5kIGRpbmluZw
5389d9f75-cc3f-4bd2-94f7-93e381a3bed5NaNNaNTmF0dXJhbCBTd2VldGVuZXJzLyBTdWdhcgTW9uayBGcnVpdAZ3JvY2VyaWVz
69599f1a9-d406-43eb-89f5-9b1c0af1ac9a$24.99NaNTW9wcyBhbmQgYnJvb21zTW9wSG91c2Vob2xkIGFuZCBDbGVhbmluZw
735799087-f6f4-4ca2-abfe-cbb5c27d2f1a$148.00NaNV29tZW5zIFBhbnRzV29tZW5zIFJlZ3VsYXIvQ2FzdWFsIFBhbnRzQ2xvdGhpbmcgYW5kIEFjY2Vzc29yaWVz
89b3f553e-ee4c-4e1c-822e-c8c6c1b7f02a$89NaNV29tZW5zIFBhbnRzV29tZW5zIFRpZ2h0cwQ2xvdGhpbmcgYW5kIEFjY2Vzc29yaWVz
96871b427-3c2c-4b3d-a304-c0a9f924439d$14.95NaNUm9sbGluZyBQaW4UGxheSBEb3VnaCBSb2xsaW5nIFBpbgVG95cyBhbmQgR2FtZXM

Last rows

uuidprice_stringprice_string_unfproduct_typelevel_1category
137299900946bab5-4f6c-49c8-860f-30956889f2abNaNNaNTWF0ZXJuaXR5IERyZXNzTWF0ZXJuaXR5IE1pZGkgZHJlc3MQ2xvdGhpbmcgYW5kIEFjY2Vzc29yaWVz
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Duplicate rows

Most frequently occurring

uuidprice_stringprice_string_unfproduct_typelevel_1category# duplicates
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843b4b57a-b225-4fd3-9326-a09096e9f7f1$6.75$6.75Q29mZmVlIEJlYW5zTGlnaHQgUm9hc3QZ3JvY2VyaWVz10000
953beedf4-ed7c-4407-9081-7ae41f3a7282$15.00$15.00RG91Z2ggSmFyUGxheWRvdWdoIC8gUGxheWRvaAVG95cyBhbmQgR2FtZXM10000